Species Distribution Modeling (SDM) and Wildlife Habitat Ratings (WHR) project boundaries contains (study areas) and attributes describing each project (project level metadata), plus links to the locations of other data associated with the project (e.g. reports, WHR polygon datasets, plotfiles). SDM predicts the suitability of different environments for occupation by particular species, and the likelihood that those suitable habitats are occupied. WHR are also known as wildlife habitat interpretations and most commonly use TEM data as a means to identify specific habitats. This layer is derived from the STE_TEI_PROJECT_BOUNDARIES_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: WHR, SDM, PEMWHR, PEMSDM, TEMWHR, TEMSDM, TEMPRW, NEMPRW, TEMSEW, BEIWHR, BEISDM, SEIWHR, SDM, and SOILSW. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.

Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.

Manitoba market hog prices and United States (U.S.) iso-wean and feeder pig prices shown weekly and monthly for current and previous years.This table contains weekly and monthly prices paid for market hogs in Manitoba and iso-wean and feeder pigs in United States (U.S.) in current and previous years, as well as average prices for five and 10 previous years.  For hog price report definitions and calculations, click here.  Manitoba market hog prices are collected from major processors in Manitoba, compiled and released weekly by Manitoba Agriculture and Resource Development (ARD). Manitoba market hog prices are weighted by the volume of hogs processed, and averaged monthly. United States (U.S.) iso-wean and feeder pig prices are sourced from the United States Department of Agriculture (USDA) and presented in Canadian dollars (C$) using the Bank of Canada exchange rate. Monthly U.S. iso-wean and feeder pig prices are a simple average of the weekly U.S. total composite weighted average prices. Average five and 10-year prices are calculated as simple averages of weekly or monthly prices. Fields included (Alias (Field name): Field description.) Period (Period): period of time to be presented on charts from the selection of Monthly and Weekly; ; PeriodNo (PeriodNo): serial number of period (1-12 for monthly presentation, 1-52 for weekly presentation); Hog category (Hog category): category of animals from the selection of U.S. feeder pigs, U.S. iso-wean pigs, Manitoba market hogs; Previous year price (Previous): animal price in corresponding period of previous year*; Current year price (Current): animal price in corresponding period of current year*; 5-year average price (Average5): animal price in corresponding period averaged over last 5 years (excluding current year)*; 10-year average price  (Average10): animal price in corresponding period averaged over last 10 years (excluding current year)*. *(C$ per head for U.S. feeder pigs and U.S. iso-wean pigs, C$ per 100 kg for Manitoba market hogs)

Timing windows are the period(s) during the year when work may be carried out in and about water bodies with the lowest risk to fish and wildlife species and habitat. Timing windows and terms and conditions vary based on regional differences in fish and wildlife species and habitat, and geography. The timing window of least risk to fish and fish habitat must be applied to all activities in water bodies, as well as tributaries that have a risk of depositing sediment into water bodies. Windows of least risk are designed to protect all fish species known to occur in a water body.

PURPOSE:This study is part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake. The main objectives are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. DESCRIPTION:Great Bear Lake, one of the largest lakes in North America, contains culturally and recreationally important fish species. Great Bear Lake is located in the sub-Arctic and Arctic Circle. As part of a two-decade series of research aimed to provide a comprehensive synthesis of the effects of harvest and environmental change on fisheries in Great Bear Lake, the main objectives of this study are to assess demographic traits and the current status of harvested species, with a focus on evaluating sustainable harvest levels of lake trout, a cold-adapted species with a relatively narrow thermal niche. As part of this research, trends in water quality and primary productivity are monitored to evaluate potential effects of change on fisheries. From 2021 to 2024, surface water temperature data was collected at depths of 0.1 to 1.0 meters using an RBR Maestro3 through partnered community-led and community/Fisheries and Oceans Canada/university partner collaborative sampling. The project has strong community involvement, including youth through the Guardian Program, to facilitate capacity building and community leadership in the long-term monitoring of Great Bear Lake fisheries and the aquatic ecosystem. This data is an extension of baseline data sets on water quality on the lake. These data will contribute to a better understanding cumulative impacts of climate change on the functioning of large northern lake ecosystems and provide a benchmark for monitoring further change. This data will be important for developing effective strategies for maintaining community-led aquatic monitoring and managing natural resources, particularly fish, which are expected to be increasingly important to communities with declines in other country foods such as caribou.We acknowledge the data were collected in the Sahtú Settlement Area and are made publicly available with the agreement of the Délı̨nę Renewable Resources Council (Délı̨nę Ɂehdzo Got’ı̨nę (Renewable Resources Council)). Collaborators include: the Community of Délı̨nę partners (data collection), Délı̨nę Renewable Resource Council, Sahtú Renewable Resource Board, and University of Manitoba. Community of Délı̨nę partners and field workers that participated in data collection include Chris Yukon, Archie Vital, Ted Mackienzo, Daniel Baton, Lloyd Baton, Simon Neyelle, and Stanley Ferdanan.Funding and logistical support was provided by: Northwest Territories Cumulative Impact Monitoring, Sahtú Renewable Resource Board, the Polar Continental Shelf Program and Fisheries and Oceans Canada.

Terrestrial Ecosystem Information Project Boundaries contains boundaries (study areas) and attributes describing each project (project level metadata), plus links to the locations of other data associated with the project (e.g., reports, polygon datasets, plotfiles, legends). TEI inventories describe the physical and biological attributes of ecosystems. TEI currently includes Terrestrial Ecosystem Mapping (TEM), Predictive Ecosystem Mapping (PEM), Sensitive Ecosystems Inventory (SEI), Terrain Mapping (TER), Soil Mapping (SOIL), Species Distribution Mapping (SDM) and Wildlife Habitat Ratings (WHR) projects. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

The Broad Ecosystem Inventory (BEI) Classification provides broad regional information about the distribution of ecosystems throughout the province and the value of these ecosystems to wildlife. This work is done in order to facilitate the use of wildlife information in broad provincial and regional land and resource planning initiatives. Broad Ecosystem Units are mapped based on imagery of the provincial land base generally captured at a scale of 1:250,000. BEI mapping represents forest conditions from approximately 1995 to 2000. The BEI Classification was used to produce wildlife habitat capability and suitability mapping following Provincial Wildlife Habitat Ratings (WHR) Standards (Resource Inventory Committee 1999). Habitat classifications were based on BEI units. BEI units were evaluated and rated to determine the habitat potential (capability) and current habitat conditions (suitability) for selected wild ungulates and furbearers within each seral stage within each Broad Ecosystem Unit (and related site modifier variation) within the framework of Ecosections and Biogeoclimatic Sub-zone/Variants for their ability to supply the species’ necessary life requisites. Regional Wildlife and Habitat biologists, technicians, Forest Ecosystem Specialists, and consulting species experts provided species habitat ratings for each region of the province. Wildlife habitat capability and suitability mapping was completed for the following wild ungulates and furbearers: Northwestern Moose, Alaskan Moose, Shiras' Moose, Bison, Rocky Mountain Elk, Roosevelt Elk, Columbian Black-tailed Deer, Rocky Mountain Mule Deer, Sitka Black-tailed Deer, White-tailed Deer, Dakota White-tailed Deer, Northwestern White-tailed Deer, Boreal Woodland Caribou, Mountain Woodland Caribou, Northern Woodland Caribou, Lynx, Bobcat, and American Badger. Habitat mapping followed Provincial Wildlife Habitat Ratings (WHR) Standards (Resource Inventory Committee 1999).

Terrain Inventory Mapping (TIM) contains polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. TIM is multi-purpose and divides the landscape into units according to surficial material, surface expression and geomorphological process using the Terrain Classification System for British Columbia. Most of the inventory mapping was completed in the 1970s and 1980s on 1 to 50,000 scale base maps using air photo interpretation with selective field checking, and manual transfer and drafting of paper maps. These maps were later digitized and have been converted from IGDS or CAPAMP to ArcInfo to Geodatabase. This layer is derived from the STE_TEI_ATTRIBUTE_POLYS_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: TIM and TIMSOI. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)

Terrain Stability Mapping (TSM) contains polygons with key and amalgamated (concatenated) attributes derived from the RISC (Resource Inventory Standards Committee) standard attributes. TSM uses air photo interpretation and select field checking to divides the landscape into units using the Terrain Classification System for British Columbia and stability criteria. Polygon attributes include (but are not limited to) surficial material, surface expression, geomorphological processes, drainage class, slope range and stability class. TSM methods include manual air photo interpretation and setting stability criteria supported by selective field checking. This layer is derived from the STE_TEI_ATTRIBUTE_POLYS_SP layer by filtering on the PROJECT_TYPE attribute. Project types include: TEMSET, TEMTSM, TSM, TSMREC, TSMDET, TBW, and TBS. Current version: v11 (published on 2024-10-03) Previous versions: v10 (published on 2023-11-14), v9 (published on 2023-03-01), v8 (published on 2016-09-01)